• ###### baseline hazard function
• The Cox partial likelihood, shown below, is obtained by using Breslow's estimate of the baseline hazard function, plugging it into the full likelihood and then observing that the result is a product of two factors. (wikipedia.org)
• ###### subset
• a missing-data filter function, applied to the model.frame, after any subset argument has been used. (psu.edu)
• Since these models generate a small prioritized list of potential defectors, they are effective at focusing customer retention marketing programs on the subset of the customer base who are most vulnerable to churn. (wikipedia.org)
• ###### partial
• The exact method computes the exact partial likelihood, which is equivalent to a conditional logistic model. (psu.edu)
• ###### biostatistics
• In biostatistics, the researcher may be interested in trying to model the probability of a patient being diagnosed with a certain type of cancer based on knowing, say, the incidence of that cancer in his or her family. (wikipedia.org)
• ###### predictors
• it makes a parametric assumption concerning the effect of the predictors on the hazard function, but makes no assumption regarding the nature of the hazard function λ( t ) itself. (springer.com)
• That is, a multiple regression model with colinear predictors can indicate how well the entire bundle of predictors predicts the outcome variable, but it may not give valid results about any individual predictor, or about which predictors are redundant with respect to others. (wikipedia.org)
• Generalized additive model is a smoothing method for multiple predictors that allows for non-parametric predictions. (wikipedia.org)
• ###### assumes
• Poisson regression assumes the response variable Y has a Poisson distribution, and assumes the logarithm of its expected value can be modeled by a linear combination of unknown parameters. (wikipedia.org)
• ###### estimates
• In this situation the coefficient estimates of the multiple regression may change erratically in response to small changes in the model or the data. (wikipedia.org)
• The log-rank test statistic compares estimates of the hazard functions of the two groups at each observed event time. (wikipedia.org)
• ###### probability
• Poisson regression models are generalized linear models with the logarithm as the (canonical) link function, and the Poisson distribution function as the assumed probability distribution of the response. (wikipedia.org)
• In many cases the model is chosen on the basis of detection theory to try to guess the probability of an outcome given a set amount of input data, for example given an email determining how likely that it is spam. (wikipedia.org)
• In business, the marketer may be interested in modelling the probability of an individual purchasing a product based on the price of that product. (wikipedia.org)
• ###### 1972
• The proportional hazards design was presented in 1972 by D. R. Cox in order to approximate the results of various covariates affecting the times to the failures of a system. (statshelponline.com)
• ###### function
• In many situations, either the form of the true hazard function is unknown or it is complex, so the Cox model has definite advantages. (springer.com)
• ###### frailty models
• Supplied penalty functions include ridge regression ( ridge ), smoothing splines ( pspline ), and frailty models ( frailty ). (psu.edu)
• ###### Nonparametric
• It may appear at first that semiparametric models include nonparametric models, since they have an infinite-dimensional as well as a finite-dimensional component. (wikipedia.org)
• In nonparametric models, by contrast, the primary interest is in estimating the infinite-dimensional parameter. (wikipedia.org)
• Thus the estimation task is statistically harder in nonparametric models. (wikipedia.org)
• ###### structural model
• The case that the x variable arises randomly is known as the structural model or structural relationship. (wikipedia.org)
• ###### approaches
• Robust regression include a number of modelling approaches to handle high leverage observations or violation of assumptions. (wikipedia.org)
• ###### assessment
• Models capture relationships among many factors to allow assessment of risk or potential associated with a particular set of conditions, guiding decision making for candidate transactions. (wikipedia.org)
• ###### 1992
• in a 1992 paper, Wei pointed out that the Buckley-James model has no theoretical justification and lacks robustness, and reviewed alternatives. (wikipedia.org)
• ###### approach
• They explain the survival inning accordance with one aspect under examination, however overlook the effect of other.An option approach is the Cox proportional hazards regression analysis , which works for both quantitative predictor variables and for categorical variables. (statshelponline.com)
• ###### predictor
• 1978). The case of multiple predictor variables subject to variability (possibly correlated) has been well-studied for linear regression, and for some non-linear regression models. (wikipedia.org)
• Other non-linear models, such as proportional hazards models for survival analysis, have been considered only with a single predictor subject to variability. (wikipedia.org)
• The model is "simple" in that each has only one independent, or predictor, variable, and it is "binary" in that the dependent variable can take on only one of two values: cancer or no cancer, and purchase or does not purchase. (wikipedia.org)
• ###### analytical
• In most applications, involuntary reasons for churn are excluded from the analytical models. (wikipedia.org)
• Deployment : Predictive model deployment provides the option to deploy the analytical results into everyday decision making process to get results, reports and output by automating the decisions based on the modelling. (wikipedia.org)
• However, people are increasingly using the term to refer to related analytical disciplines, such as descriptive modeling and decision modeling or optimization. (wikipedia.org)
• ###### prediction models
• More sophisticated predictive analytics software use churn prediction models that predict customer churn by assessing their propensity of risk to churn. (wikipedia.org)
• By deploying new technologies such churn prediction models coupled with effective retention programs, customer attrition could be better managed to stem the significant revenue loss from defecting customers. (wikipedia.org)
• The log-rank test has been shown to be too permissive a test, allowing significant results for survivorship prediction models that have low accuracy. (wikipedia.org)
• ###### robust
• term is used to compute a robust variance for the model. (psu.edu)
• ###### Known
• The case that x is fixed, but measured with noise, is known as the functional model or functional relationship. (wikipedia.org)
• A Poisson regression model is sometimes known as a log-linear model, especially when used to model contingency tables. (wikipedia.org)
• The traditional negative binomial regression model, commonly known as NB2, is based on the Poisson-gamma mixture distribution. (wikipedia.org)